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Old 03-15-2014, 11:29 AM   #9
sazz
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Location: Istanbul, Turkey

Join Date: Oct 2012
Posts: 28
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Quote:
Originally Posted by dalesan View Post
Sure thing, sazz. Maybe by the end of next week I'll have something to share.
Well, I have already made a comparison btw genome and transcriptome mapping, while all the other parameters were exactly same.

First of all; in my experiment, I have control and target shRNA transduced cell line (human) and for my RNA-seq, I prepared 3 replicates from each. Total read number for all is around 110M (Single End, 50bp).

I run Tophat with -g 1 option to get uniquely mapped reads. (it was ~70% hit for transcriptome mapping)

When I compared CuffDiff output btw those 2 approach;
There are 1983 significantly differentially expressed genes (q<0.01) in intersection and 107 for only whole genome mapping, and 94 for only transcriptome mapping.

So for my data, if there is a difference, it seems like a small one and I don't think it will make a change in downstream analysis (I haven't tried yet.)
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